Response of Chickpea Cultivars to Imidazolinone Herbicide Applied at Different Growth Stages
Bibliographic record
Abstract
POST broadleaf weed control options in chickpea are very limited on the Northern Great Plains. Field experiments were conducted in 2012 and 2013 in Saskatchewan to evaluate the response of chickpea cultivars to imidazolinone (IMI) herbicides applied at different growth stages. Conventional cultivars ‘CDC Luna’ and ‘CDC Corinne’ were compared with IMI-resistant cultivars ‘CDC Alma’ and ‘CDC Cory’. Treatments comprised a combination of imazethapyr + imazamox herbicides at 30 and 60 g ai ha−1(1× and 2× rates, respectively) applied at the 2 to 4-, 5 to 8-, and 9 to 12-node growth stages. Visual injury estimates were > 50% for CDC Luna and CDC Corinne for all growth stage applications. Conventional cultivars also experienced height reduction and decreased rate of node development compared with the nontreated controls. Flowering and maturity of CDC Luna and CDC Corinne were delayed for herbicide applications at all growth stages; however, application at the 9 to 12-node stage caused the most severe delay. All treatments of IMI herbicide caused yield reduction in the conventional cultivars in 2013. In contrast, IMI-resistant cultivars CDC Alma and CDC Cory demonstrated no negative response at any growth stage of IMI herbicide application. Visual injury estimates were negligible, and height, node development, days to flowering, maturity, and yield did not differ significantly between IMI-treated plants and the respective controls. These results demonstrated the potential of in-crop use of IMI herbicide on resistant chickpea cultivars to control broadleaf weeds.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".